QC plots

QC, raw data

## $CellCount

## 
## $UMI

## 
## $nFeature

## 
## $PercentMT

## 
## $GenesPerUMI

## 
## $nFeature_vs_nCount.MT
## `geom_smooth()` using formula 'y ~ x'

## 
## $nFeature_vs_nCount.SingleR
## `geom_smooth()` using formula 'y ~ x'

QC, filtered data

Data filtered via: nFeature_RNA > 1000 & percent.mt < 15

## $CellCount

## 
## $UMI

## 
## $nFeature

## 
## $PercentMT

## 
## $GenesPerUMI

## 
## $nFeature_vs_nCount.MT
## `geom_smooth()` using formula 'y ~ x'

## 
## $nFeature_vs_nCount.SingleR
## `geom_smooth()` using formula 'y ~ x'

Cell type predictions

Azimuth predictions

Doublet detection

Number of methods detecting doublets

Number of methods dectecting doublets by cell type in all samples, unfiltered vs filtered data

Number of methods dectecting doublets by cell type, split samples, unfiltered vs filtered data

Scrublet results

All samples

Scrublet doublet detection in all samples, unfilt vs filt

By sample

Scrublet doublet detection, split samples, unfilt vs filt

Doublet finder results

All samples

Doublet finder detection in all samples, unfilt vs filt

By sample

Doublet finder detection, split samples, unfilt vs filt

Clustering

Unfiltered data

Clustering unfiltered data, non-integrated

Label sample

Label cluster

Label cell type

Label doublet finder doublets

Label scrublet doublets

Filtered data

Clustering filtered, integrated data with resolution = 1

Label sample

Label cluster

Label cell type

Label doublet finder doublets

Label scrublet doublets